Volatility Modeling Workshop

TOOLS & TECHNIQUES: Quantitative Analysis Track

Excel Focused Technical Skill Development

2 DAY COURSE

Qualifies for CPD and 14 CPE Credits

INTRODUCTION

Forecasting volatility accurately has become the key issue in pricing the financial instruments and the risk as well as in designing optimum risk management mechanisms. This intensive and interactive training course is designed for entry to intermediate level professionals, with limited knowledge of volatility and volatility modeling within the risk management perspective. At the end of this course participants will be specialized on volatility modeling, perhaps one of the most important tools in risk management. The training will be focused on model building through Excel/VBA spreadsheet.

Who should attend?

This intensive and interactive course is designed for intermediate to advanced level professionals who are exposed to volatility such as risk managers, traders, sales professionals, financial analysts, cash/money managers, auditors and compliance professionals.

What will you get out of this course?

• Learn the key elements of statistics and probability for successful forecasting

• Implementation of volatility estimation methods

• Experience different volatility models

• Construct effective volatility models

• Use volatility models for hedging

COURSE OVERVIEW AND OUTLINE

For this intensive and highly interactive course, all delegates are strongly recommended to attend the workshop with a laptop computer loaded with Microsoft Excel.

Foundations of probability and deterministic volatility

• Price and return data

• Functions of random variables, multivariate distribution functions, important distribution functions and moments, timescales

• Basic parameter estimation

• Regressions and sampling error, drift and volatility

• Variable volatility delta hedging

• Real and risk neutral, the continuous-time limit

Volatility estimation: Simple statistical methods

• Moving windows, mean reverting, exponentially weighted moving average, parameter estimation by maximum likelihood, expected volatility, GARCH, Parkinson's number, geometric implementation of volatilities and correlations, Monte Carlo methods

• Application in Excel

Examination of volatility models

• Deterministic volatility models, Stochastic volatility models, jumps and Lévy processes, empirical study of volatility, Heston model

• Local volatility models

• Fokker-Planck equation, Tanaka’s formula, arbitrage portfolio, forward equation for options, implied volatility, problems with smile

• Stochastic volatility models

• Local volatility as expectation of future instantaneous volatility, correlation, spot dependency and mean reversion, Heath-Jarrow-Morton Treatment, calibrated Markov models

• Jump diffusion models

• Need of jumps, stochastic volatility model with jumps, Merton model and extensions

• Market models of implied volatility

• Modeling the dynamics of implied volatility, current approaches, implied versus local volatility, arbitrage conditions

• Application in Excel

Volatility calibration and arbitrage

• Theoretical skewness, time-dependent volatility, risk-neutral density, non-arbitrageable smile moves, locking implied volatilities

Hedging volatility risk

• Decomposing through superbucket analysis

• Optimal static hedging

• Monte Carlo multiple regression

• Gamma projection

Reconstructing volatility

• Volatility surfaces of single stocks and equity indices

• Generating one-factor models

• Varadhan’s Formula and the Steepest Descent Approximation (SDA)

• Reconstructing the implied volatility skew of different products

• Application in Excel